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.gitattributes

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README.md

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+---
+tags:
+- ctranslate2
+- translation
+license: cc-by-4.0
+---
+# # Fast-Inference with Ctranslate2
+Speedup inference by 2x-8x using int8 inference in C++
+
+quantized version of [Helsinki-NLP/opus-mt-en-de](https://huggingface.co/Helsinki-NLP/opus-mt-en-de)
+```bash
+pip install hf-hub-ctranslate2>=1.0.0 ctranslate2>=3.13.0
+```
+Converted using
+```
+ct2-transformers-converter --model Helsinki-NLP/opus-mt-en-de --output_dir /home/michael/tmp-ct2fast-opus-mt-en-de --force --copy_files README.md generation_config.json tokenizer_config.json vocab.json source.spm .gitattributes target.spm --quantization float16
+```
+
+Checkpoint compatible to [ctranslate2](https://github.com/OpenNMT/CTranslate2) and [hf-hub-ctranslate2](https://github.com/michaelfeil/hf-hub-ctranslate2)
+- `compute_type=int8_float16` for `device="cuda"` 
+- `compute_type=int8`  for `device="cpu"`
+
+```python
+from hf_hub_ctranslate2 import TranslatorCT2fromHfHub, GeneratorCT2fromHfHub
+from transformers import AutoTokenizer
+
+model_name = "michaelfeil/ct2fast-opus-mt-en-de"
+# use either TranslatorCT2fromHfHub or GeneratorCT2fromHfHub here, depending on model.
+model = TranslatorCT2fromHfHub(
+        # load in int8 on CUDA
+        model_name_or_path=model_name, 
+        device="cuda",
+        compute_type="int8_float16",
+        tokenizer=AutoTokenizer.from_pretrained("Helsinki-NLP/opus-mt-en-de")
+)
+outputs = model.generate(
+    text=["How do you call a fast Flan-ingo?", "User: How are you doing?"],
+)
+print(outputs)
+```
+
+# Licence and other remarks:
+This is just a quantized version. Licence conditions are intended to be idential to original huggingface repo.
+
+# Original description
+    
+
+### opus-mt-en-de
+
+
+## Table of Contents
+- [Model Details](#model-details)
+- [Uses](#uses)
+- [Risks, Limitations and Biases](#risks-limitations-and-biases)
+- [Training](#training)
+- [Evaluation](#evaluation)
+- [Citation Information](#citation-information)
+- [How to Get Started With the Model](#how-to-get-started-with-the-model)
+
+## Model Details
+**Model Description:**
+- **Developed by:** Language Technology Research Group at the University of Helsinki
+- **Model Type:** Translation
+- **Language(s):**  
+  - Source Language: English
+  - Target Language: German 
+- **License:** CC-BY-4.0
+- **Resources for more information:**
+  - [GitHub Repo](https://github.com/Helsinki-NLP/OPUS-MT-train)
+  
+
+## Uses
+
+#### Direct Use
+
+This model can be used for translation and text-to-text generation.
+
+
+## Risks, Limitations and Biases
+
+
+
+**CONTENT WARNING: Readers should be aware this section contains content that is disturbing, offensive, and can propagate historical and current stereotypes.**
+
+Significant research has explored bias and fairness issues with language models (see, e.g., [Sheng et al. (2021)](https://aclanthology.org/2021.acl-long.330.pdf) and [Bender et al. (2021)](https://dl.acm.org/doi/pdf/10.1145/3442188.3445922)).
+
+Further details about the dataset for this model can be found in the OPUS readme: [en-de](https://github.com/Helsinki-NLP/OPUS-MT-train/blob/master/models/en-de/README.md)
+
+
+#### Training Data
+##### Preprocessing
+* pre-processing: normalization + SentencePiece
+
+* dataset: [opus](https://github.com/Helsinki-NLP/Opus-MT)
+* download original weights: [opus-2020-02-26.zip](https://object.pouta.csc.fi/OPUS-MT-models/en-de/opus-2020-02-26.zip)
+
+* test set translations: [opus-2020-02-26.test.txt](https://object.pouta.csc.fi/OPUS-MT-models/en-de/opus-2020-02-26.test.txt)
+
+## Evaluation
+
+#### Results
+
+* test set scores: [opus-2020-02-26.eval.txt](https://object.pouta.csc.fi/OPUS-MT-models/en-de/opus-2020-02-26.eval.txt)
+
+
+#### Benchmarks
+
+| testset               | BLEU  | chr-F |
+|-----------------------|-------|-------|
+| newssyscomb2009.en.de 	| 23.5 	| 0.540 |
+| news-test2008.en.de 	| 23.5 	| 0.529 |
+| newstest2009.en.de 	| 22.3 	| 0.530 |
+| newstest2010.en.de 	| 24.9 	| 0.544 |
+| newstest2011.en.de 	| 22.5 	| 0.524 |
+| newstest2012.en.de 	| 23.0 	| 0.525 |
+| newstest2013.en.de 	| 26.9 	| 0.553 |
+| newstest2015-ende.en.de 	| 31.1 	| 0.594 |
+| newstest2016-ende.en.de 	| 37.0 	| 0.636 |
+| newstest2017-ende.en.de 	| 29.9 	| 0.586 |
+| newstest2018-ende.en.de 	| 45.2 	| 0.690 |
+| newstest2019-ende.en.de 	| 40.9 	| 0.654 |
+| Tatoeba.en.de 	| 47.3 	| 0.664 |
+
+
+
+## Citation Information
+
+```bibtex
+@InProceedings{TiedemannThottingal:EAMT2020,
+  author = {J{\"o}rg Tiedemann and Santhosh Thottingal},
+  title = {{OPUS-MT} — {B}uilding open translation services for the {W}orld},
+  booktitle = {Proceedings of the 22nd Annual Conferenec of the European Association for Machine Translation (EAMT)},
+  year = {2020},
+  address = {Lisbon, Portugal}
+ }
+```
+
+## How to Get Started With the Model
+```python
+from transformers import AutoTokenizer, AutoModelForSeq2SeqLM
+
+tokenizer = AutoTokenizer.from_pretrained("Helsinki-NLP/opus-mt-en-de")
+
+model = AutoModelForSeq2SeqLM.from_pretrained("Helsinki-NLP/opus-mt-en-de")
+
+```
+
+
+
+

config.json

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+{
+  "add_source_bos": false,
+  "add_source_eos": false,
+  "bos_token": "<s>",
+  "decoder_start_token": "</s>",
+  "eos_token": "</s>",
+  "unk_token": "<unk>"
+}

generation_config.json

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+{
+  "_from_model_config": true,
+  "bad_words_ids": [
+    [
+      58100
+    ]
+  ],
+  "bos_token_id": 0,
+  "decoder_start_token_id": 58100,
+  "eos_token_id": 0,
+  "forced_eos_token_id": 0,
+  "max_length": 512,
+  "num_beams": 4,
+  "pad_token_id": 58100,
+  "transformers_version": "4.27.0.dev0"
+}

model.bin

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tokenizer_config.json

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+{"target_lang": "de", "source_lang": "en"}